code: def test_mp(args, model, test_samplers, rank=0, mode="Test"):
      if args.num_proc > 1:
          th.set_num_threads(args.num_thread)
      test(args, model, test_samplers, 0, rank, mode)
  
imports: import torch.multiprocessing
  from torch.utils.data import DataLoader
  import torch.optim
  import torch
  from distutils.version import LooseVersion
  from .models.pytorch.tensor_models import thread_wrapped_func
  from .models import KEModel
  from .utils import save_model, get_compatible_batch_size
  import os
  import logging
  import time
  from functools import wraps
  import dgl
  from dgl.contrib import KVClient
  import dgl.backend
  from .dataloader import EvalDataset
  from .dataloader import get_dataset
  import pdb
  from collections import defaultdict
  from ogb.lsc import WikiKG90MDataset, WikiKG90MEvaluator
  from tqdm.auto import tqdm
  import pickle
  from math import ceil
label_desc: Use image node_id 6 for calling a global function with example usage: test_mp(args, model, test_samplers, rank, mode) without return types